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| Filter results12 paper(s) found. |
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1. Factors Related To Adoption Of Precision Agriculture Technologies In Southern BrazilThe adoption of technologies which allow the increase of food production with improving quality in addition to reduce the foot prints in the environment is important for agribusiness development. Precision Agriculture (PA) stands out as an option to aid the achievement of these goals. Brazil plays an important role to supply agricultural products and to demand technologies. However, research has focused on technical and economic implementation of PA technologies. Therefore, more information... A.A. Anselmi, L.C. Federizzi , C. Bredemeier, J.P. Molin |
2. Precision Nutrient Management System Based on Ion and Crop Growth SensingAutomated sensing and variable-rate supply of nutrients in hydroponic solutions according to the status of crop growth would allow more efficient nutrient management for crop growth in closed systems. The Structure from Motion (SfM) method has risen as a new image sensing method to obtain 3D images of plants that can be used to estimate their growth, such as leaf cover area (LCA), plant height, and fresh weight. In this sense, sensor fusion technology combining ion-selective electrodes (ISEs)... W. Cho, D. Kim, C. Kang, H. Kim, J. Son, S. Chung, J. Jiang, H. Yun |
3. Wheat Biomass Estimation Using Visible Aerial Images and Artificial Neural NetworkIn this study, visible RGB-based vegetation indices (VIs) from UAV high spatial resolution (1.9 cm) remote sensing images were used for modeling shoot biomass of two Brazilian wheat varieties (TBIO Toruk and BRS Parrudo). The approach consists of a combination of Artificial Neural Network (ANN) with several Vegetation Indices to model the measured crop biomass at different growth stages. Several vegetation indices were implemented: NGRDI (Normalized Green-Red Difference Index), CIVE (Color Index... M.R. De Souza, T.D. Bertani, A. Parraga, C. Bredemeier, C. Trentin, D. Doering, A. Susin, M. Negreiros |
4. Influence of Application Rate and Flight Orientation on Droplet Deposition by Remotely Piloted Aircraft (RPA) in ‘Gala’ Apple OrchardsApple production is a cornerstone of the fruit industry, with the ‘Gala’ variety holding a prominent position due to its commercial value. However, this cultivar is highly susceptible to apple scab (Venturia inaequalis), requiring application technologies of fungicides that ensure canopy protection, especially during flowering. In this sense, precision horticulture has sought alternatives to optimize the application of crop protection products, aiming to reduce... L. Espindola Müller, T. Buchener, B. Nogueira, R. Silva, S.J. Silveira, C. Bredemeier |
5. Analysis of Mixed Models in UAV-based Spectral Vegetation Indices for Prediction of Agronomic Variables in Soybean Subjected to FloodingThe identification of soybean genotypes with increased flooding tolerance is relevant for yield stability in lowlands producing areas. In this context, the use of relevant spectral vegetation indices based on multispectral sensors embedded in unmanned aerial vehicles (UAVs) for the selection of more flooding-tolerant soybean genotypes is a primary demand within plant phenomics. Nonetheless, the environmental effects can change the accuracy of spectral indices and the correct methodology for deduction... C.D. Lima, B. Nogueira, A. , D.U. Junior, I.R. Carvalho, C. Bredemeier |
6. Cotton Yield Response to Seed Density in Contrasting Productive Potential ZonesABSTRACT: Brazilian cotton farming has high economic and agricultural importance. However, it faces challenges related to management practices that consider the spatial variability of productivity across different yield potential zones within a field. In this sense, precision agriculture tools have great potential to optimize and rationalize input use in areas with spatial variability in productive potential, especially through the use of variable rate seeding. Nevertheless, studies... G. , C. Bredemeier, R. , D. |
7. Importance of Irradiance Correction for UAV-based Vegetation Indices in the Prediction of Shoot Biomass in WheatThe extraction of vegetation indices from multispectral images obtained with UAV-bsed sensors for biomass estimation has proven to be a useful tool for designing site-specific interventions on wheat. The reflectance values from monochromatic bands collected with optical sensors for calculating vegetation indices should have high reliability and repeatability in the case of successive assessments under different illumination conditions. In this context, the objective of the study was to characterize... A.C. Figueiró, B. Nogueira, E. Bender, R. Silva, V.M. Cassol, S.J. Silveira , C. Bredemeier, A.L. Vian |
8. Estimation of Agronomic Parameters in Maize Using UAV-based Vegetation Indices Obtained by a Multispectral SensorPrecision agriculture emerges as a response to optimize input use and to monitor crop spatial variability over time. In this context, the use of vegetation indices obtained by optical sensors embedded in drones or satellites has become a useful tool for predicting agronomic parameters in maize fields, such as aboveground dry biomass, leaf chlorophyll content, and grain yield. Thus, the objective of this study was to correlate field agronomic parameters with vegetation indexes obtained by a multispectral... B. Nogueira, A.C. Figueiró, A. , E. Bender, C.D. Lima, A.L. Vian, C. Bredemeier |
9. Integration of Spectrotemporal Metrics and Machine Learning for Soybean Grain Yield PredictionEstimating agricultural grain yield in heterogeneous production environments remains one of the main challenges of digital agriculture. Although vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Red Edge (NDRE), are widely used to describe canopy vigor, their predictive capacity strongly depends on how temporal information is represented and on the structure of the model employed to integrate this spectral variability. The present study... L. Rossetto Gerlach, A.L. Vian, C. Bredemeier, T. Enderle, T. Santos Cocco, M. Wrubleski |
10. Selection of UAV-based Vegetation Indices for the Prediction of Leaf Chlorophyll Content in Maize Using a Normalized Partial Least Squares Regression (PLSR) Reduction ApproachThe accurate monitoring of the nutritional status is essential for optimizing nitrogen (N) fertilization and maximizing maize grain yield. Variations in N availability directly affect agronomic parameters such as leaf chlorophyll content, which can be estimated using optical sensors. This study assessed the effects of urease inhibitors and nitrogen application rates on leaf chlorophyll content and predicted total leaf chlorophyll content in maize using relevant vegetation indices under field conditions.... B. Nogueira, E. Bender, D. De Carvalho Arruda, M. Da Costa Salem, L. Espindola Muller, S.R. Dos Santos Gonçalves Junior, G. Eissmann Souza, J.V. Muller Klassmann, B.B. Gallo, C. Bredemeier |
11. Estimation of carbon sequestration in agricultural crops using the C-Questro softwareContemporary agriculture faces the challenge of reconciling productivity with climate impact mitigation, positioning soil and plant biomass carbon sequestration as a strategic pillar for global sustainability. However, carbon quantification at the field scale still encounters hurdles due to high-cost methodologies or operational complexity. The objective of this work was to develop and validate a Python-based software, named "C-Questro," designed to automate the estimation of carbon... |
12. Hyperspectral Imagery for Prediction of Leaf Chlorophyll Content in Maize Under the Application of Different Urease Inhibitors Using Machine LearningUrea is the most common and widely used nitrogen (N) source. However, it is highly susceptible to ammonia volatilization losses, especially under favorable climatic conditions. The use of urease inhibitors becomes an important strategy because these compounds slow down the hydrolysis of urea, increasing efficiency in terms of N assimilation, enhancing leaf chlorophyll content, promoting plant growth, and maximizing maize grain yield. In parallel, hyperspectral sensors have emerged as a non-destructive... S.R. Gonçalves Junior, M. Da Costa Salem, G. Eissmann Souza, D. Carvalho De Arruda, E. Bender, B. Nogueira, L. Espindola Muller, B.B. Gallo, C. Bredemeier |